Age-Specific Clinical Biomarker Ranges in Acute Head Injury, Non-TBI Trauma, and Healthy Control Subjects in the...

Blood-based biomarkers for traumatic brain injury (TBI) are increasingly integrated into diagnostic algorithms, but their interpretation may be confounded by age-related neurological changes. This study quantified the relative effects of age and TBI on biomarker concentrations to determine whether age-related variation approaches or exceeds that associated with injury.

Serum biomarkers were analyzed from 762 adults enrolled in the HeadSMART II and HeadSMART Geriatric studies, including healthy controls (n = 88), non-head trauma controls (n = 99), and mild TBI patients (GCS 13-15, n = 575). Participants were categorized by age (18-40, 41-64, 65-74, ≥ 75 years). Six TBI-relevant biomarkers (glial fibrillary acidic protein [GFAP], brain-derived neurotrophic factor [BDNF], neurogranin [NRGN], α-synuclein [SNCA], suppression of tumorigenicity 2 [ST2], and von Willebrand factor [vWF]) were quantified using validated immunoassays (BRAINBox Solutions). Biomarker levels were compared using two-way ANOVA, and the relative effects of age and injury were estimated using Cohen's f.

Age significantly influenced several biomarkers. GFAP showed strong age-related increases, with significant elevations across age strata (p < 0.001), exceeding the effect of head injury alone. vWF also increased significantly with age (p < 0.001), while ST2 did not show a main effect of age (p = 0.404), although age interacted with group (p < 0.001). SNCA demonstrated modest age effects (p = 0.001), particularly in older trauma and TBI participants. NRGN showed no significant age-related changes (p = 0.454), and BDNF exhibited age effects within interaction terms (p < 0.001). Overall, age-associated effect sizes for GFAP and vWF were comparable to, or greater than, those of head injury.

Age exerts substantial influence on circulating biomarker concentrations, particularly GFAP and vWF, often rivaling or exceeding TBI-related changes. Diagnostic algorithms that fail to adjust for age may risk misclassification, especially among older adults, underscoring the need for age-normalized biomarker interpretation.